Study Of Community Detection Problem In Signed Networks

With the continuous development of Internet technology and the advent of the era of big data,complex networks have become an important direction for scholars at home and abroad.At present,according to the different relationships between entities in complex networks,complex networks are divided into signed networks and unsigned networks.signed networks are networks that have both positive and negative relationships.For example,in real life,the relationship between friends and enemies between individuals,competition and cooperation,positive and negative relationships,and trust and distrust relationships.Mining community structures in social networks is an important basis for studying signed networks;at the same time,it is also of great significance for theoretical research and applications such as data analysis,relationship prediction,and feature analysis.Therefore,this paper combines the current research status of community detection of signed networks and the problems existing in community detection,the main innovative work and research results are as follows.First,based on the structural balance theory and combining the properties of the signed network structure,this paper obtains a method for calculating the propagation strength.Based on the propagation strength and the label propagation algorithm,a new signed network community detection algorithm is proposed.The algorithm is applied to the non-overlapping community detection of signed networks.In addition,the experimental results verify the accuracy and effectiveness of the algorithm.Secondly,this paper proposes a signed network community detection algorithm based on node trust.This algorithm first calculates the node trust in the signed network,and then divides the community structure of the symbol network according to the size and direction of the node trust.The experimental results show that the signed The combination of the positive and negative relationships of the network and the trust of the nodes can accurately and efficiently divide the community structure of the signed network.Finally,a reasonable signed network overlap community detection algorithm is proposed based on the direction of node trust.The main idea of the algorithm is to find the core nodes in the network based on the direction of node trust,determine the community division according to the core nodes,and then find overlapping nodes through different communities to determine overlapping communities.At the same time,the accuracy of the algorithm is verified by experimental results.